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README.md

@@ -7,49 +7,32 @@ library_name: transformers
 
 # Matformer Model
 
-This model was trained using the [Matformer](https://github.com/mrinaldi97/matformer) library.
-
-## Model Type
-- **Architecture**: causal
+Trained using [Matformer](https://github.com/mrinaldi97/matformer).
 
 ## Installation
 
-First, install the required package:
-
 ```bash
 pip install git+https://github.com/mrinaldi97/matformer.git
 ```
 
-Or set the `MATFORMER_ROOT` environment variable:
-
-```bash
-export MATFORMER_ROOT=/path/to/matformer
-```
-
 ## Usage
 
 ```python
 import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoModelForCausalLM
 
-# Load model
 model = AutoModelForCausalLM.from_pretrained(
     "mrinaldi/prova001",
     trust_remote_code=True
 )
 
-# Generate text
 prompt = "The transformer model is a"
-inputs = model.tokenizer.encode(prompt, add_bos=True, add_eos=False)
-inputs = torch.tensor([inputs], device=model.device)
+inputs = model.matformer_model.tokenizer.encode(prompt, add_bos=True, add_eos=False)
+inputs = torch.tensor([inputs], device="cuda")
 
 with torch.no_grad():
     outputs = model.generate(inputs, max_new_tokens=50)
     
-decoded = model.tokenizer.decode(outputs[0].tolist())
+decoded = model.matformer_model.tokenizer.decode(outputs[0].tolist())
 print(decoded)
 ```
-
-## Citation
-
-If you use this model, please cite the Matformer library.

checkpoint.ckpt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eac3a5928e878a5327f30f584767bbd2beed08c96d05b714498fa72b5f8e3e21
+size 1340947056

config.json

@@ -1,5 +1,9 @@
 {
+  "_checkpoint_path": "../checkpoints_baby_BUONO/last-v2.ckpt",
   "_matformer_config_dict": {
+    "_checkpoint_path": "../checkpoints_baby_BUONO/last-v2.ckpt",
+    "_model_class": "Autoregressive_Model",
+    "_tokenizer_name": "sapienzanlp/Minerva-350M-base-v1.0",
     "attention_type": [],
     "bias": false,
     "block_size_for_attention": 128,
@@ -31,6 +35,7 @@
     "name": "BabyLM",
     "num_attention_heads": 12,
     "num_hidden_layers": 12,
+    "num_labels": 2,
     "pad_token_id": 0,
     "rms_norm_eps": 1e-06,
     "rope_theta": 10000.0,
@@ -39,9 +44,8 @@
     "training_objective": "autoregressive",
     "vocab_size": 32777
   },
-  "architectures": [
-    "MatformerForCausalLM"
-  ],
+  "_model_class": "Autoregressive_Model",
+  "_tokenizer_name": "sapienzanlp/Minerva-350M-base-v1.0",
   "attention_type": [],
   "auto_map": {
     "AutoConfig": "modeling_matformer.MatformerConfig",
@@ -83,7 +87,6 @@
   "rms_norm_eps": 1e-06,
   "rope_theta": 10000.0,
   "sliding_type": null,
-  "torch_dtype": "bfloat16",
   "training_objective": "autoregressive",
   "transformers_version": "4.53.0.dev0",
   "use_cache": true,

modeling_matformer.py

@@ -1,9 +1,7 @@
 # modeling_matformer.py
-# Auto-generated by Matformer integration for Hugging Face Hub compatibility
 import os
 import sys
 
-# Try to import matformer from environment
 matformer_root = os.getenv("MATFORMER_ROOT")
 if matformer_root:
     matformer_root = os.path.abspath(os.path.expanduser(matformer_root))
@@ -24,19 +22,13 @@ except ImportError as e:
     import subprocess
     import tempfile
     
-    print("Matformer not found. Attempting to install from GitHub...")
+    print("Installing Matformer from GitHub...")
     try:
-        print("DEBUG")
-        print(os.getcwd())
+        subprocess.check_call([
+            sys.executable, "-m", "pip", "install", 
+            "git+https://github.com/mrinaldi97/matformer.git"
+        ])
         
-
-        with tempfile.TemporaryDirectory() as tmpdir:
-            subprocess.check_call([
-                sys.executable, "-m", "pip", "install", 
-                "git+https://github.com/mrinaldi97/matformer.git"
-            ])
-        
-        # Try importing again
         from matformer.modelling_matformer import (
             MatformerForCausalLM,
             MatformerForMaskedLM,
@@ -46,12 +38,10 @@ except ImportError as e:
             register_matformer
         )
         register_matformer()
-        print("Successfully installed and imported Matformer!")
         
     except Exception as install_error:
         raise ImportError(
-            "Failed to install Matformer automatically. Please install manually:\n"
+            "Failed to install Matformer. Install manually:\n"
             "  pip install git+https://github.com/mrinaldi97/matformer.git\n"
-            "Or set the MATFORMER_ROOT environment variable to a local clone:\n"
-            "  export MATFORMER_ROOT=/path/to/matformer"
+            "Or set MATFORMER_ROOT environment variable"
         ) from install_error